{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import glob\n",
    "import tensorflow as tf\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 训练和测试数据的存储地址\n",
    "train_data_path = 'D:/Desktop/hand writer/dataset/test_CASIA_Image/Train'\n",
    "test_data_path = 'D:/Desktop/hand writer/dataset/test_CASIA_Image/Test'\n",
    "# 训练手写体图片的存储地址\n",
    "train_image_path = glob.glob(train_data_path + '/*/*.jpg')\n",
    "# 提取手写体图片的标签\n",
    "train_labels = [p.split(\"Train\\\\\")[1].split(\"\\\\\")[0] for p in train_image_path]\n",
    "# 根据计算机cpu的个数自动做并行运算\n",
    "AUTOTUNE =tf.data.experimental.AUTOTUNE"
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "def convert_to_one_hot(data_path, labels, split_str):\n",
    "    # 读取所有汉字目录\n",
    "    label_path = glob.glob(data_path + '/*')\n",
    "    # 对汉字目录进行处理，生成汉字标签列表\n",
    "    label_strs = np.array([lp.split(split_str)[1] for lp in label_path])\n",
    "    # 创建一个存放one-hot标签的二维零矩阵\n",
    "    vector = np.zeros((len(labels), len(label_path)))\n",
    "    # 对所有的汉字标签进行处理，将其一一转为one-hot编码\n",
    "    for i in range(len(labels)):\n",
    "        vector[i, label_strs.tolist().index(labels[i])] = 1\n",
    "    return len(label_strs), vector"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 将汉字转为数字标签\n",
    "def convert_to_number(data_path, labels_character, split_str):\n",
    "    # 读取所有汉字目录\n",
    "    label_path = glob.glob(data_path + '/*')\n",
    "    # 对汉字目录进行处理，获取所有的汉字列表\n",
    "    label_strs = np.array([lp.split(split_str)[1] for lp in label_path])\n",
    "    # 创建一个行数为图片总数，列数为1的零矩阵\n",
    "    len_labels_character = len(labels_character)\n",
    "    vector = np.zeros((len_labels_character, 1))\n",
    "    # 对所有图片对应的汉字标签进行处理，将其一一转为对应的数字\n",
    "    for i in range(len_labels_character):\n",
    "        vector[i, 0] = label_strs.tolist().index(labels_character[i])\n",
    "    return len(label_strs), vector"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 通过路径读取图片\n",
    "def load_preprosess_image(path, label):\n",
    "    image = tf.io.read_file(path)\n",
    "    # 解码\n",
    "    image = tf.image.decode_jpeg(image, channels=1)\n",
    "    # 将图像处理成相同大小\n",
    "    image = tf.image.resize(image, [96, 96])\n",
    "    # 改变数据类型\n",
    "    image = tf.cast(image, tf.float32)\n",
    "    # 归一化\n",
    "    image = image / 255\n",
    "\n",
    "    #label = tf.reshape(label, (545, 10))\n",
    "    # label = tf.reshape(label, (1, train_count * num_label))\n",
    "    return image, label"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 训练手写体图片的存储地址\n",
    "train_image_path = glob.glob(train_data_path + '/*/*.jpg')\n",
    "# p = \"D:\\\\Desktop\\\\hand writer\\\\CASIA_Dataset_Image\\\\Gnt 1.0Train\\\\艇\\\\162903.jpg\"\n",
    "# 提取手写体图片的标签，标签为所有汉字列表\n",
    "train_image_labels = [p.split(\"Train\\\\\")[1].split(\"\\\\\")[0] for p in train_image_path]\n",
    "# 将所有的汉字转为数字编码\n",
    "num_labels, train_num_labels = convert_to_number(train_data_path, train_image_labels, \"Train\\\\\")\n",
    "train_num_labels = tf.cast(train_num_labels, tf.int32)\n",
    "\n",
    "# 创建dataset训练对象\n",
    "train_image_ds = tf.data.Dataset.from_tensor_slices((train_image_path, np.array(train_num_labels)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<TensorSliceDataset shapes: ((), (1,)), types: (tf.string, tf.int32)>"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train_image_ds"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [],
   "source": [
    "train_image_ds = train_image_ds.map(load_preprosess_image, num_parallel_calls=AUTOTUNE)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<ParallelMapDataset shapes: ((96, 96, 1), (1,)), types: (tf.float32, tf.int32)>"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train_image_ds"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [],
   "source": [
    "imgs, labels = next(iter(train_image_ds))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
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   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       " 'D:/Desktop/hand writer/dataset/test_CASIA_Image/Train\\\\叭\\\\6801.jpg',\n",
       " 'D:/Desktop/hand writer/dataset/test_CASIA_Image/Train\\\\叭\\\\70582.jpg',\n",
       " 'D:/Desktop/hand writer/dataset/test_CASIA_Image/Train\\\\叭\\\\72696.jpg',\n",
       " 'D:/Desktop/hand writer/dataset/test_CASIA_Image/Train\\\\叭\\\\77729.jpg',\n",
       " 'D:/Desktop/hand writer/dataset/test_CASIA_Image/Train\\\\叭\\\\81113.jpg',\n",
       " 'D:/Desktop/hand writer/dataset/test_CASIA_Image/Train\\\\叭\\\\8265.jpg',\n",
       " 'D:/Desktop/hand writer/dataset/test_CASIA_Image/Train\\\\叭\\\\87735.jpg',\n",
       " 'D:/Desktop/hand writer/dataset/test_CASIA_Image/Train\\\\叭\\\\91122.jpg',\n",
       " 'D:/Desktop/hand writer/dataset/test_CASIA_Image/Train\\\\叭\\\\95786.jpg',\n",
       " 'D:/Desktop/hand writer/dataset/test_CASIA_Image/Train\\\\叭\\\\97876.jpg',\n",
       " 'D:/Desktop/hand writer/dataset/test_CASIA_Image/Train\\\\吧\\\\103838.jpg',\n",
       " 'D:/Desktop/hand writer/dataset/test_CASIA_Image/Train\\\\吧\\\\106571.jpg',\n",
       " 'D:/Desktop/hand writer/dataset/test_CASIA_Image/Train\\\\吧\\\\111877.jpg',\n",
       " 'D:/Desktop/hand writer/dataset/test_CASIA_Image/Train\\\\吧\\\\113961.jpg',\n",
       " 'D:/Desktop/hand writer/dataset/test_CASIA_Image/Train\\\\吧\\\\119152.jpg',\n",
       " 'D:/Desktop/hand writer/dataset/test_CASIA_Image/Train\\\\吧\\\\12298.jpg',\n",
       " 'D:/Desktop/hand writer/dataset/test_CASIA_Image/Train\\\\吧\\\\123814.jpg',\n",
       " 'D:/Desktop/hand writer/dataset/test_CASIA_Image/Train\\\\吧\\\\126536.jpg',\n",
       " 'D:/Desktop/hand writer/dataset/test_CASIA_Image/Train\\\\吧\\\\130564.jpg',\n",
       " 'D:/Desktop/hand writer/dataset/test_CASIA_Image/Train\\\\吧\\\\135869.jpg',\n",
       " 'D:/Desktop/hand writer/dataset/test_CASIA_Image/Train\\\\吧\\\\139241.jpg',\n",
       " 'D:/Desktop/hand writer/dataset/test_CASIA_Image/Train\\\\吧\\\\141979.jpg',\n",
       " 'D:/Desktop/hand writer/dataset/test_CASIA_Image/Train\\\\吧\\\\144741.jpg',\n",
       " 'D:/Desktop/hand writer/dataset/test_CASIA_Image/Train\\\\吧\\\\148778.jpg',\n",
       " 'D:/Desktop/hand writer/dataset/test_CASIA_Image/Train\\\\吧\\\\153431.jpg',\n",
       " 'D:/Desktop/hand writer/dataset/test_CASIA_Image/Train\\\\吧\\\\159403.jpg',\n",
       " 'D:/Desktop/hand writer/dataset/test_CASIA_Image/Train\\\\吧\\\\16330.jpg',\n",
       " 'D:/Desktop/hand writer/dataset/test_CASIA_Image/Train\\\\吧\\\\164083.jpg',\n",
       " 'D:/Desktop/hand writer/dataset/test_CASIA_Image/Train\\\\吧\\\\166817.jpg',\n",
       " 'D:/Desktop/hand writer/dataset/test_CASIA_Image/Train\\\\吧\\\\170193.jpg',\n",
       " 'D:/Desktop/hand writer/dataset/test_CASIA_Image/Train\\\\吧\\\\176137.jpg',\n",
       " 'D:/Desktop/hand writer/dataset/test_CASIA_Image/Train\\\\吧\\\\179518.jpg',\n",
       " 'D:/Desktop/hand writer/dataset/test_CASIA_Image/Train\\\\吧\\\\184161.jpg',\n",
       " 'D:/Desktop/hand writer/dataset/test_CASIA_Image/Train\\\\吧\\\\186237.jpg',\n",
       " 'D:/Desktop/hand writer/dataset/test_CASIA_Image/Train\\\\吧\\\\190900.jpg',\n",
       " 'D:/Desktop/hand writer/dataset/test_CASIA_Image/Train\\\\吧\\\\193001.jpg',\n",
       " 'D:/Desktop/hand writer/dataset/test_CASIA_Image/Train\\\\吧\\\\197032.jpg',\n",
       " 'D:/Desktop/hand writer/dataset/test_CASIA_Image/Train\\\\吧\\\\203619.jpg',\n",
       " 'D:/Desktop/hand writer/dataset/test_CASIA_Image/Train\\\\吧\\\\206352.jpg',\n",
       " 'D:/Desktop/hand writer/dataset/test_CASIA_Image/Train\\\\吧\\\\209112.jpg',\n",
       " 'D:/Desktop/hand writer/dataset/test_CASIA_Image/Train\\\\吧\\\\20992.jpg',\n",
       " 'D:/Desktop/hand writer/dataset/test_CASIA_Image/Train\\\\吧\\\\213763.jpg',\n",
       " 'D:/Desktop/hand writer/dataset/test_CASIA_Image/Train\\\\吧\\\\219084.jpg',\n",
       " 'D:/Desktop/hand writer/dataset/test_CASIA_Image/Train\\\\吧\\\\25025.jpg',\n",
       " 'D:/Desktop/hand writer/dataset/test_CASIA_Image/Train\\\\吧\\\\29058.jpg',\n",
       " 'D:/Desktop/hand writer/dataset/test_CASIA_Image/Train\\\\吧\\\\32464.jpg',\n",
       " 'D:/Desktop/hand writer/dataset/test_CASIA_Image/Train\\\\吧\\\\3420.jpg',\n",
       " 'D:/Desktop/hand writer/dataset/test_CASIA_Image/Train\\\\吧\\\\37126.jpg',\n",
       " 'D:/Desktop/hand writer/dataset/test_CASIA_Image/Train\\\\吧\\\\42450.jpg',\n",
       " 'D:/Desktop/hand writer/dataset/test_CASIA_Image/Train\\\\吧\\\\44562.jpg',\n",
       " 'D:/Desktop/hand writer/dataset/test_CASIA_Image/Train\\\\吧\\\\49201.jpg',\n",
       " 'D:/Desktop/hand writer/dataset/test_CASIA_Image/Train\\\\吧\\\\59131.jpg',\n",
       " 'D:/Desktop/hand writer/dataset/test_CASIA_Image/Train\\\\吧\\\\62514.jpg',\n",
       " 'D:/Desktop/hand writer/dataset/test_CASIA_Image/Train\\\\吧\\\\64629.jpg',\n",
       " 'D:/Desktop/hand writer/dataset/test_CASIA_Image/Train\\\\吧\\\\6802.jpg',\n",
       " 'D:/Desktop/hand writer/dataset/test_CASIA_Image/Train\\\\吧\\\\70583.jpg',\n",
       " 'D:/Desktop/hand writer/dataset/test_CASIA_Image/Train\\\\吧\\\\72697.jpg',\n",
       " 'D:/Desktop/hand writer/dataset/test_CASIA_Image/Train\\\\吧\\\\77730.jpg',\n",
       " 'D:/Desktop/hand writer/dataset/test_CASIA_Image/Train\\\\吧\\\\81114.jpg',\n",
       " 'D:/Desktop/hand writer/dataset/test_CASIA_Image/Train\\\\吧\\\\8266.jpg',\n",
       " 'D:/Desktop/hand writer/dataset/test_CASIA_Image/Train\\\\吧\\\\87736.jpg',\n",
       " 'D:/Desktop/hand writer/dataset/test_CASIA_Image/Train\\\\吧\\\\91123.jpg',\n",
       " 'D:/Desktop/hand writer/dataset/test_CASIA_Image/Train\\\\吧\\\\95787.jpg',\n",
       " 'D:/Desktop/hand writer/dataset/test_CASIA_Image/Train\\\\吧\\\\97877.jpg',\n",
       " 'D:/Desktop/hand writer/dataset/test_CASIA_Image/Train\\\\哀\\\\103804.jpg',\n",
       " 'D:/Desktop/hand writer/dataset/test_CASIA_Image/Train\\\\哀\\\\106537.jpg',\n",
       " 'D:/Desktop/hand writer/dataset/test_CASIA_Image/Train\\\\哀\\\\111843.jpg',\n",
       " 'D:/Desktop/hand writer/dataset/test_CASIA_Image/Train\\\\哀\\\\113927.jpg',\n",
       " 'D:/Desktop/hand writer/dataset/test_CASIA_Image/Train\\\\哀\\\\119118.jpg',\n",
       " 'D:/Desktop/hand writer/dataset/test_CASIA_Image/Train\\\\哀\\\\12264.jpg',\n",
       " 'D:/Desktop/hand writer/dataset/test_CASIA_Image/Train\\\\哀\\\\123780.jpg',\n",
       " 'D:/Desktop/hand writer/dataset/test_CASIA_Image/Train\\\\哀\\\\126502.jpg',\n",
       " 'D:/Desktop/hand writer/dataset/test_CASIA_Image/Train\\\\哀\\\\130530.jpg',\n",
       " 'D:/Desktop/hand writer/dataset/test_CASIA_Image/Train\\\\哀\\\\135835.jpg',\n",
       " 'D:/Desktop/hand writer/dataset/test_CASIA_Image/Train\\\\哀\\\\139207.jpg',\n",
       " 'D:/Desktop/hand writer/dataset/test_CASIA_Image/Train\\\\哀\\\\141945.jpg',\n",
       " 'D:/Desktop/hand writer/dataset/test_CASIA_Image/Train\\\\哀\\\\144707.jpg',\n",
       " 'D:/Desktop/hand writer/dataset/test_CASIA_Image/Train\\\\哀\\\\148744.jpg',\n",
       " 'D:/Desktop/hand writer/dataset/test_CASIA_Image/Train\\\\哀\\\\153397.jpg',\n",
       " 'D:/Desktop/hand writer/dataset/test_CASIA_Image/Train\\\\哀\\\\159369.jpg',\n",
       " 'D:/Desktop/hand writer/dataset/test_CASIA_Image/Train\\\\哀\\\\16296.jpg',\n",
       " 'D:/Desktop/hand writer/dataset/test_CASIA_Image/Train\\\\哀\\\\164049.jpg',\n",
       " 'D:/Desktop/hand writer/dataset/test_CASIA_Image/Train\\\\哀\\\\166783.jpg',\n",
       " 'D:/Desktop/hand writer/dataset/test_CASIA_Image/Train\\\\哀\\\\170159.jpg',\n",
       " 'D:/Desktop/hand writer/dataset/test_CASIA_Image/Train\\\\哀\\\\176103.jpg',\n",
       " 'D:/Desktop/hand writer/dataset/test_CASIA_Image/Train\\\\哀\\\\179484.jpg',\n",
       " 'D:/Desktop/hand writer/dataset/test_CASIA_Image/Train\\\\哀\\\\184127.jpg',\n",
       " 'D:/Desktop/hand writer/dataset/test_CASIA_Image/Train\\\\哀\\\\186203.jpg',\n",
       " 'D:/Desktop/hand writer/dataset/test_CASIA_Image/Train\\\\哀\\\\190866.jpg',\n",
       " 'D:/Desktop/hand writer/dataset/test_CASIA_Image/Train\\\\哀\\\\192967.jpg',\n",
       " 'D:/Desktop/hand writer/dataset/test_CASIA_Image/Train\\\\哀\\\\196998.jpg',\n",
       " 'D:/Desktop/hand writer/dataset/test_CASIA_Image/Train\\\\哀\\\\203585.jpg',\n",
       " 'D:/Desktop/hand writer/dataset/test_CASIA_Image/Train\\\\哀\\\\206318.jpg',\n",
       " 'D:/Desktop/hand writer/dataset/test_CASIA_Image/Train\\\\哀\\\\209078.jpg',\n",
       " 'D:/Desktop/hand writer/dataset/test_CASIA_Image/Train\\\\哀\\\\20958.jpg',\n",
       " 'D:/Desktop/hand writer/dataset/test_CASIA_Image/Train\\\\哀\\\\213729.jpg',\n",
       " 'D:/Desktop/hand writer/dataset/test_CASIA_Image/Train\\\\哀\\\\219050.jpg',\n",
       " 'D:/Desktop/hand writer/dataset/test_CASIA_Image/Train\\\\哀\\\\24991.jpg',\n",
       " 'D:/Desktop/hand writer/dataset/test_CASIA_Image/Train\\\\哀\\\\29024.jpg',\n",
       " 'D:/Desktop/hand writer/dataset/test_CASIA_Image/Train\\\\哀\\\\32430.jpg',\n",
       " 'D:/Desktop/hand writer/dataset/test_CASIA_Image/Train\\\\哀\\\\3386.jpg',\n",
       " 'D:/Desktop/hand writer/dataset/test_CASIA_Image/Train\\\\哀\\\\37092.jpg',\n",
       " 'D:/Desktop/hand writer/dataset/test_CASIA_Image/Train\\\\哀\\\\42416.jpg',\n",
       " 'D:/Desktop/hand writer/dataset/test_CASIA_Image/Train\\\\哀\\\\44528.jpg',\n",
       " 'D:/Desktop/hand writer/dataset/test_CASIA_Image/Train\\\\哀\\\\49167.jpg',\n",
       " 'D:/Desktop/hand writer/dataset/test_CASIA_Image/Train\\\\哀\\\\59097.jpg',\n",
       " 'D:/Desktop/hand writer/dataset/test_CASIA_Image/Train\\\\哀\\\\62480.jpg',\n",
       " 'D:/Desktop/hand writer/dataset/test_CASIA_Image/Train\\\\哀\\\\64595.jpg',\n",
       " 'D:/Desktop/hand writer/dataset/test_CASIA_Image/Train\\\\哀\\\\6768.jpg',\n",
       " 'D:/Desktop/hand writer/dataset/test_CASIA_Image/Train\\\\哀\\\\70549.jpg',\n",
       " 'D:/Desktop/hand writer/dataset/test_CASIA_Image/Train\\\\哀\\\\72663.jpg',\n",
       " 'D:/Desktop/hand writer/dataset/test_CASIA_Image/Train\\\\哀\\\\77696.jpg',\n",
       " 'D:/Desktop/hand writer/dataset/test_CASIA_Image/Train\\\\哀\\\\81080.jpg',\n",
       " 'D:/Desktop/hand writer/dataset/test_CASIA_Image/Train\\\\哀\\\\8232.jpg',\n",
       " 'D:/Desktop/hand writer/dataset/test_CASIA_Image/Train\\\\哀\\\\87702.jpg',\n",
       " 'D:/Desktop/hand writer/dataset/test_CASIA_Image/Train\\\\哀\\\\91089.jpg',\n",
       " 'D:/Desktop/hand writer/dataset/test_CASIA_Image/Train\\\\哀\\\\95753.jpg',\n",
       " 'D:/Desktop/hand writer/dataset/test_CASIA_Image/Train\\\\哀\\\\97843.jpg',\n",
       " 'D:/Desktop/hand writer/dataset/test_CASIA_Image/Train\\\\哎\\\\103802.jpg',\n",
       " 'D:/Desktop/hand writer/dataset/test_CASIA_Image/Train\\\\哎\\\\106535.jpg',\n",
       " 'D:/Desktop/hand writer/dataset/test_CASIA_Image/Train\\\\哎\\\\111841.jpg',\n",
       " 'D:/Desktop/hand writer/dataset/test_CASIA_Image/Train\\\\哎\\\\113925.jpg',\n",
       " 'D:/Desktop/hand writer/dataset/test_CASIA_Image/Train\\\\哎\\\\119116.jpg',\n",
       " 'D:/Desktop/hand writer/dataset/test_CASIA_Image/Train\\\\哎\\\\12262.jpg',\n",
       " 'D:/Desktop/hand writer/dataset/test_CASIA_Image/Train\\\\哎\\\\123778.jpg',\n",
       " 'D:/Desktop/hand writer/dataset/test_CASIA_Image/Train\\\\哎\\\\126500.jpg',\n",
       " 'D:/Desktop/hand writer/dataset/test_CASIA_Image/Train\\\\哎\\\\130528.jpg',\n",
       " 'D:/Desktop/hand writer/dataset/test_CASIA_Image/Train\\\\哎\\\\135833.jpg',\n",
       " 'D:/Desktop/hand writer/dataset/test_CASIA_Image/Train\\\\哎\\\\139205.jpg',\n",
       " 'D:/Desktop/hand writer/dataset/test_CASIA_Image/Train\\\\哎\\\\141943.jpg',\n",
       " 'D:/Desktop/hand writer/dataset/test_CASIA_Image/Train\\\\哎\\\\144705.jpg',\n",
       " 'D:/Desktop/hand writer/dataset/test_CASIA_Image/Train\\\\哎\\\\148742.jpg',\n",
       " 'D:/Desktop/hand writer/dataset/test_CASIA_Image/Train\\\\哎\\\\153395.jpg',\n",
       " 'D:/Desktop/hand writer/dataset/test_CASIA_Image/Train\\\\哎\\\\159367.jpg',\n",
       " 'D:/Desktop/hand writer/dataset/test_CASIA_Image/Train\\\\哎\\\\16294.jpg',\n",
       " 'D:/Desktop/hand writer/dataset/test_CASIA_Image/Train\\\\哎\\\\164047.jpg',\n",
       " ...]"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train_image_path"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "598"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "test_image_path = glob.glob(test_data_path + '/*/*.jpg')\n",
    "len(test_image_path)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "598"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "test_image_label = [p.split(\"Test\\\\\")[1].split(\"\\\\\")[0] for p in test_image_path]\n",
    "len(test_image_label)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "ename": "NameError",
     "evalue": "name 'convert_to_one_hot' is not defined",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mNameError\u001b[0m                                 Traceback (most recent call last)",
      "\u001b[1;32m<ipython-input-14-dec831c7f162>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m\u001b[0m\n\u001b[0;32m      2\u001b[0m \u001b[0mtest_image_label\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;33m[\u001b[0m\u001b[0mp\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0msplit\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m\"Test\\\\\"\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;36m1\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0msplit\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m\"\\\\\"\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;36m0\u001b[0m\u001b[1;33m]\u001b[0m \u001b[1;32mfor\u001b[0m \u001b[0mp\u001b[0m \u001b[1;32min\u001b[0m \u001b[0mtest_image_path\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m      3\u001b[0m \u001b[1;31m# 将所有的汉字标签列表转为one-hot编码\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m----> 4\u001b[1;33m \u001b[0mnum\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mtest_label_onehot\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mconvert_to_one_hot\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mtest_data_path\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mtest_image_label\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;34m\"Test\\\\\"\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m      5\u001b[0m \u001b[1;31m# 创建dataset训练对象\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m      6\u001b[0m \u001b[1;31m#test_image_ds = tf.data.Dataset.from_tensor_slices((test_image_path, test_label_onehot))\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;31mNameError\u001b[0m: name 'convert_to_one_hot' is not defined"
     ]
    }
   ],
   "source": [
    "test_image_path = glob.glob(test_data_path + '/*/*.jpg')\n",
    "test_image_label = [p.split(\"Test\\\\\")[1].split(\"\\\\\")[0] for p in test_image_path]\n",
    "# 将所有的汉字标签列表转为one-hot编码\n",
    "num, test_label_onehot = convert_to_one_hot(test_data_path, test_image_label, \"Test\\\\\")\n",
    "# 创建dataset训练对象\n",
    "#test_image_ds = tf.data.Dataset.from_tensor_slices((test_image_path, test_label_onehot))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "test_image_ds = tf.data.Dataset.from_tensor_slices((test_image_path, test_label_onehot))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "len(test_image_ds)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "def convert_to_one_hot(data_path, labels, split_str):\n",
    "    # 读取所有汉字目录\n",
    "    label_path = glob.glob(data_path + '/*')\n",
    "    # 对汉字目录进行处理，生成汉字标签列表\n",
    "    label_strs = np.array([lp.split(split_str)[1] for lp in label_path])\n",
    "    # 创建一个存放one-hot标签的二维零矩阵\n",
    "    vector = np.zeros((len(labels), len(label_path)))\n",
    "    # 对所有的汉字标签进行处理，将其一一转为one-hot编码\n",
    "    for i in range(len(labels)):\n",
    "        vector[i, label_strs.tolist().index(labels[i])] = 1\n",
    "    return len(label_strs),vector"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "vector = convert_to_one_hot(train_labels)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "len(vector)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "train_image_ds = tf.data.Dataset.from_tensor_slices((train_image_path,train_labels))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "len(train_image_ds)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "train_image_ds = train_image_ds.map(load_preprosess_image,num_parallel_calls=AUTOTUNE)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "train_image_ds"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "model= tf.keras.Sequential() # 顺序模型\n",
    "# 第一层使用卷积层，卷积层提取图片特征的能力强   32-fliter个数  (3,3)-卷积核大小，一般使用3*3或5*5  input_shape-图片大小\n",
    "model.add(tf.keras.layers.Conv2D(64,(3,3),input_shape=train_images.shape[1:],activation='relu',padding='same'))\n",
    "model.add(tf.keras.layers.Conv2D(64,(3,3),activation='relu',padding='same'))\n",
    "# 最大池化层\n",
    "model.add(tf.keras.layers.MaxPool2D())\n",
    "# 抑制过拟合\n",
    "model.add(tf.keras.layers.Dropout(0.5))\n",
    "# 卷积核以2的指数增长\n",
    "model.add(tf.keras.layers.Conv2D(128,(3,3),activation='relu',padding='same'))\n",
    "model.add(tf.keras.layers.Conv2D(128,(3,3),activation='relu',padding='same'))\n",
    "# 最大池化层\n",
    "model.add(tf.keras.layers.MaxPool2D())\n",
    "# 抑制过拟合\n",
    "model.add(tf.keras.layers.Dropout(0.5))\n",
    "model.add(tf.keras.layers.Conv2D(256,(3,3),activation='relu',padding='same'))\n",
    "model.add(tf.keras.layers.Conv2D(256,(3,3),activation='relu',padding='same'))\n",
    "# 抑制过拟合\n",
    "model.add(tf.keras.layers.Dropout(0.5))\n",
    "# 全局平均池化：得到一个二维的数据\n",
    "model.add(tf.keras.layers.GlobalAveragePooling2D())\n",
    "# Dense 输出层：输出一个维度为10的数据  softmax:输出概率值\n",
    "model.add(tf.keras.layers.Dense(256,activation='relu'))\n",
    "model.add(tf.keras.layers.Dense(10,activation='softmax'))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "p = ['D:/Desktop/hand writer/dataset/test_CASIA_Image/Train\\\\呸\\\\101968.jpg', 'D:/Desktop/hand writer/dataset/test_CASIA_Image/Train\\\\呸\\\\10254.jpg', 'D:/Desktop/hand writer/dataset/test_CASIA_Image/Train\\\\呸\\\\104702.jpg', 'D:/Desktop/hand writer/dataset/test_CASIA_Image/Train\\\\呸\\\\110010.jpg', 'D:/Desktop/hand writer/dataset/test_CASIA_Image/Train\\\\呸\\\\115940.jpg', 'D:/Desktop/hand writer/dataset/test_CASIA_Image/Train\\\\呸\\\\117395.jpg', 'D:/Desktop/hand writer/dataset/test_CASIA_Image/Train\\\\呸\\\\121952.jpg', 'D:/Desktop/hand writer/dataset/test_CASIA_Image/Train\\\\呸\\\\124668.jpg', 'D:/Desktop/hand writer/dataset/test_CASIA_Image/Train\\\\呸\\\\128689.jpg', 'D:/Desktop/hand writer/dataset/test_CASIA_Image/Train\\\\呸\\\\134003.jpg', 'D:/Desktop/hand writer/dataset/test_CASIA_Image/Train\\\\呸\\\\137368.jpg', 'D:/Desktop/hand writer/dataset/test_CASIA_Image/Train\\\\呸\\\\14283.jpg', 'D:/Desktop/hand writer/dataset/test_CASIA_Image/Train\\\\呸\\\\143968.jpg', 'D:/Desktop/hand writer/dataset/test_CASIA_Image/Train\\\\呸\\\\146730.jpg']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "l = [[1, 0, 0, 0, 0, 0, 0, 0, 0, 0],[1, 0, 0, 0, 0, 0, 0, 0, 0, 0],[1, 0, 0, 0, 0, 0, 0, 0, 0, 0],[1, 0, 0, 0, 0, 0, 0, 0, 0, 0],[1, 0, 0, 0, 0, 0, 0, 0, 0, 0],[1, 0, 0, 0, 0, 0, 0, 0, 0, 0],[1, 0, 0, 0, 0, 0, 0, 0, 0, 0],[1, 0, 0, 0, 0, 0, 0, 0, 0, 0],[1, 0, 0, 0, 0, 0, 0, 0, 0, 0],[1, 0, 0, 0, 0, 0, 0, 0, 0, 0],[1, 0, 0, 0, 0, 0, 0, 0, 0, 0],[1, 0, 0, 0, 0, 0, 0, 0, 0, 0],[1, 0, 0, 0, 0, 0, 0, 0, 0, 0],[1, 0, 0, 0, 0, 0, 0, 0, 0, 0]]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "ds = tf.data.Dataset.from_tensor_slices((p,l))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "ds"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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